Simulation of Nonlinear Systems Trajectories: between Models and Behaviors

Fuente: arXiv
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Main Authors: Fazzi, Antonio, Chiuso, Alessandro
Format: Preprint
Published: 2023
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author Fazzi, Antonio
Chiuso, Alessandro
author_facet Fazzi, Antonio
Chiuso, Alessandro
contents In this paper, we study connections between the classical model-based approach to nonlinear system theory, where systems are represented by equations, and the nonlinear behavioral approach, where systems are defined as sets of trajectories. In particular, we focus on equivalent representations of the systems in the two frameworks for the problem of simulating a future nonlinear system trajectory starting from a given set of noisy data. The goal also includes extending some existing results from the deterministic to the stochastic setting.
format Preprint
id arxiv_https___arxiv_org_abs_2304_02930
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Simulation of Nonlinear Systems Trajectories: between Models and Behaviors
Fazzi, Antonio
Chiuso, Alessandro
Optimization and Control
In this paper, we study connections between the classical model-based approach to nonlinear system theory, where systems are represented by equations, and the nonlinear behavioral approach, where systems are defined as sets of trajectories. In particular, we focus on equivalent representations of the systems in the two frameworks for the problem of simulating a future nonlinear system trajectory starting from a given set of noisy data. The goal also includes extending some existing results from the deterministic to the stochastic setting.
title Simulation of Nonlinear Systems Trajectories: between Models and Behaviors
topic Optimization and Control
url https://arxiv.org/abs/2304.02930